Incorporating Spectral Shaping Filtering into DWT-Based Vector Modulation to Improve Blind Audio Watermarking
- 162 Downloads
A spectral shaping technique emerging from autoregressive modeling is incorporated into vector modulation to achieve efficient blind audio watermarking. This technique allows the watermarking process to be performed in a broader frequency band with the embedding strength adapting to auditory masking thresholds. To ensure accurate watermark retrieval, we slacken the condition for binary embedding and develop an iterative algorithm to carry out energy-balanced vector modulation. As a result, the proposed scheme reaches a capacity as high as 818.26 bits per second but still possesses sufficient robustness and transparency. The effectiveness of the proposed scheme has been demonstrated using the perceptual evaluation of audio quality (PEAQ) and bit error rates of recovered watermarks. The PEAQ confirms that the watermarked audio signal is perceptually indistinguishable from the original one. Compared with other recently developed DWT-based methods with less payload capacities, the proposed scheme can achieve comparable, if not better, robustness for attacks such as resampling, requantization, amplitude scaling, noise corruption, lowpass filtering, DA/AD conversion, echo addition, jittering and MPEG-3 compression.
KeywordsBlind audio watermarking Discrete wavelet transform Spectral shaping filter Human auditory masking Payload capacity
This research work was supported by the Ministry of Science and Technology, Taiwan, ROC under Grant MOST 103-2221-E-197-020.
- 1.He, X. (2008). Watermarking in audio: Key techniques and technologies. Youngstown, NY: Cambria Press.Google Scholar
- 16.Li, X., & Yu, H. H. (2000) Transparent and robust audio data hiding in cepstrum domain, In IEEE international conference on multimedia and expo (pp. 397–400), New York, NY.Google Scholar
- 28.Pandit, S. M., & Wu, S.-M. (2001). Time series and system analysis with applications. Malabar, Fl: Krieger Pub. Co.Google Scholar
- 30.Schroeder, M. R., & Atal, B. S. (1985) Code-excited linear prediction (CELP): High-quality speech at very low bit rates, In IEEE international conference on acoustics, speech, and signal processing (pp. 937–940), Tampa, FL.Google Scholar
- 32.Kabal, P. (2002). An examination and interpretation of ITU-R BS.1387: Perceptual evaluation of audio quality, TSP lab technical report, Department Electrical and Computer Engineering, McGill University.Google Scholar
- 33.Xiang, S. (2011). Audio watermarking robust against D/A and A/D conversions. EURASIP Journal on Advances in Signal Processing, 1, 1–14.Google Scholar